Design and general structure of the UVC machine
In this study, priority was given to developing and arranging the speed control of a machine, along with managing lamps during UVC applications. The machine is designed to move along heating pipes (rails) in greenhouses. The developed UVC machine autonomously navigates along predefined rail paths within the greenhouse. While the current system requires the user to determine which rail to use, all other functions—including speed adjustments and UVC dosage control—are fully automated. Its bottom structure is similar to that of a harvest cart or trolley, but it utilizes more powerful batteries for the lamps.
In total, eight lamps with a wavelength of 254 nm were planned to be assembled on the machine, with four lamps on each side. The selected lamps are 145 W each, 1.5 m long, and equipped with reflectors, as illustrated in Fig. 2(a). In addition, 1.5-meter-long UVC lamps were selected to ensure homogeneous irradiation across different plant heights. Uniform UVC exposure on leaf surfaces is critical for effective disease control in greenhouse crops. Shorter lamps may result in insufficient light penetration for taller plants; therefore, 1.5-meter lamps were preferred. Moreover, the choice of 145 W lamp power, although recommended by the manufacturer, is also scientifically justified. Flores Gallegos26 demonstrated that higher-power UVC lamps enhance operational efficiency by reducing application time. Compared to lower-power alternatives, 145 W lamps optimize microbial inactivation by delivering the required UVC dose in a shorter duration without the potential to damage crop leaves.
Technical drawing showing the front (a) and side (b) views of the UVC machine that was developed and tested.
The ballasts operate between 120 V and 277 V; at 120 V, the amperage is 1.30 A, and at 277 V, it is 0.56 A. The machine is powered by both electric motors and lamps, utilizing four 12 V/95Ah batteries. The charging unit operates at 8 A and includes current and heat control features. A green light indicates that the batteries are charging, while a red light signals that the batteries have not been connected to the charging unit for 36 h. The charging process for all four batteries takes 24 h, and once fully charged, the batteries enter protection mode. The power for the lamps is managed by two 24 V relays, which respond to data from a microprocessor. An 1800 W modified sine wave inverter converts DC power from the batteries to AC power for the electric motors and lamps.
The front view of the UVC machine, including its main frames and components, is illustrated in Fig. 1. The machine is designed to move along heating pipes, allowing for adjustable distances between the lamps and crops, as well as varying lamp heights for different crop applications. This adjustment can be easily achieved through the use of a telescopic steel profile that operates on both sides of the machine. From a technical perspective, the machine frame and lamp positions are symmetrical.
The primary sizes of the UVC machine: (a) general view of the UVC machine developed, (b) bottom view of the machine, (c) side view of the machine (photos and drawings not on scale).
Motor and motion control system
The machine is equipped with three 24 V, 350 W electric motors along with three drive brushless DC motor (BLDC) 350 W motor driver cards, as illustrated in Fig. 2(b). Pulse Width Modulation (PWM) signals from the microprocessor control the speed and direction of the motors. Additionally, limit switches are installed at both the front and back of the machine to facilitate automatic forward and backward movement. A Broadcom Wi-Fi chipset (BCM43362) and an STM32F205 120 MHz ARM Cortex M3 microcontroller were chosen for the remote control of machine movement and lamp operation. The system operates on a real-time operating system, FreeRTOS. For programming the microcontroller, the C + + programming language was used. Web and mobile applications were developed using JavaScript and mobile SDKs. The user interface is cloud-based, allowing control from any location with an internet connection.
UVC measurement method and sensor usage
For the measurement of UVC radiation between 220 and 280 nm, a Delta Ohm HD 2102.2 model data logger and a LP471UVC sensor were utilized. This device is capable of measuring UVC radiation in various units. The UVC sensor was positioned approximately 1.5 m above the ground, at the midpoint of the lamps, with a distance of about 15 cm between the lamps and the sensor. This setup simulates the distance from the machine to the crop leaves in an actual greenhouse. Measurements were taken at night, as illustrated in Fig. 3, to replicate the conditions of UVC application in greenhouses during nighttime.
Measurement Setup in the Greenhouse with rail heating pipes during the day(a) and measurements at night while the UVC machine is in action(b).
Testing of the UVC machine and speed calibration
After assembling all components and manufacturing the machine, it was tested on heating rails in a trial greenhouse. The UVC light was measured and recorded for different machine speeds, which were controlled via PWM from a mobile phone using a Wi-Fi connection. The speed of the machine was calibrated using a chronometer, converting PWM values into meters per second (m/s). A table was created to correlate UVC measurements with machine speeds in m/s.
For testing, the primary independent variable was the PWM speed, with four levels: 900, 1000, 1200, and 1300. The dependent variable was the UVC dose measured for a single lamp. The UVC intensity was recorded at various distances and machine speeds using a calibrated sensor placed at the height of the crop canopy. Measurements were conducted under controlled environmental conditions, ensuring no interference from external light sources. Each measurement was repeated three times to account for variability, and the average values were used for further analysis.
The motor driver board for the UVC machine is illustrated in Fig. 4. The device, “Brushless Motor Controller, 5V-36V 350 W DC Brushless Motor Board Safe Motor Controller BLDC PWM Driver Board,” is designed to control and drive the BLDC with a power range of 5 V to 36 V and a maximum output of 350 W. This device operates using PWM to manage motor speed by adjusting the duty cycle of the PWM signal, as noted by Yuniarto et al.27,28.
The BLDC motor driver board with power regulation and control circuitry.
Electrical and control system
The board is equipped with several safety features to protect both the motor and the board itself. These features include overcurrent protection, overvoltage protection, and thermal protection. Additionally, there is reverse polarity protection to prevent motor damage from incorrect polarity connections. This aspect is crucial when selecting BLDC motors for robotics applications.
One area where BLDC motors excel is in control system performance, specifically in torque and position control for one-wheel self-balancing vehicles29. The board is compact and easy to install, compatible with various types of brushless DC motors. It is suitable for a range of applications, including electric vehicles, drones, and industrial machinery30.
Remote control and software infrastructure
The Particle Photon is a compact and cost-effective development board with Wi-Fi capability, making it ideal for IoT applications31,32,33. It features a microcontroller, Wi-Fi module, and multiple digital/analog inputs and outputs, enabling seamless interaction with sensors, actuators, and other devices. The board is programmable via Particle’s web-based IDE or using C + + and JavaScript, and supports integration with third-party software tools (Alsekh & Hagem, 2021).
The software development follows a modular architecture to ensure scalability, real-time control, and secure cloud integration. The system consists of three main components: an embedded system software, a cloud-based API, and a user interface. The embedded software, developed in C++, manages motor control, sensor data acquisition, and safety monitoring. The RESTful API (Node.js) processes sensor data and executes remote commands, while the user interface, built using JavaScript, HTML and CSS, enables real-time visualization and remote device management. The system operates using a state-machine-based architecture, where UVC lamp activation and machine movement adjust dynamically based on pre-programmed schedules and real-time sensor feedback, optimizing UVC dose application. Supplementary File 1 illustrates the overall software architecture and data flow.
The diagrams for the microcontroller block and its electrical connections (pinout) are presented in Fig. 5.
(a) Joint Test Action Group interface connector with optional pull-up resistors for signal stabilization, (b) pin layout, and (c) physical pinout of the Particle Photon board showing analog, digital, and power pins along with setup and reset buttons.
Motor movement is controlled by several pins, each serving a specific function:
D0: Controls forward movement by triggering the motor to move forward. D1: Controls backward movement, activating the motor to move backward. D2: Manages the operational state of the motor. It starts the motor when an ‘On’ command is received and stops it with an ‘Off’ command. D3 and D: Used for sensor inputs, these pins handle interrupts that track the motor’s rotation count. They trigger interrupts when they receive signals to change the motor’s direction. D5: Controls the opening and closing of lamps on the right side of the machine. D6: Controls the opening and closing of lamps on the left side of the machine. DAC pin: Regulates the motor speed in an analog manner. The value written to this pin using “analogWrite( )” determines the speed of the motor.
The motor’s operation is managed via the D2 pin, which is initially set to a high (HIGH) state. When the motor is running, either the D0 or D1 pin is activated based on the command for forward or backward movement. Speed and direction changes for the motor are facilitated through analog signals sent via the DAC pin. Rotation signals from the sensors then control the direction changes of the motor and increase the rotation count.
Statistical analysis
All statistical analyses were conducted using SPSS v.23. Statistical analyses were performed to evaluate the relationship between PWM speed, exposure time, and UVC dose. A one-way analysis of variance (ANOVA) was conducted to determine whether there were statistically significant differences in UVC dose across different PWM speed settings. Additionally, a multivariate analysis of variance (MANOVA) was applied to assess the combined effect of PWM speed and exposure time on UVC dose distribution. Normality of the data was tested using the Shapiro-Wilk test before conducting ANOVA and MANOVA. The significance level was set at p < 0.05. Regression analysis was performed to model the relationship between PWM speed and UVC dose accumulation. An initial linear regression analysis did not yield statistically significant results (p > 0.05), so a quadratic regression model was applied, providing a better fit.